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Word Embeddings

Word embedding is the collective name for a set of language modeling and feature learning techniques in natural language processing (NLP) where words or phrases from the vocabulary are mapped to vectors of real numbers.

Techniques for learning word embeddings can include Word2Vec, GloVe, and other neural network-based approaches that train on an NLP task such as language modeling or document classification.

( Image credit: Dynamic Word Embedding for Evolving Semantic Discovery )

Papers

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Showing 1001–1025 of 4002 papers

TitleStatusHype
Metaphor Interpretation Using Word Embeddings—0
Deriving Contextualised Semantic Features from BERT (and Other Transformer Model) Embeddings—0
Decoding Brain Activity Associated with Literal and Metaphoric Sentence Comprehension Using Distributional Semantic Models—0
Decoding Word Embeddings with Brain-Based Semantic Features—0
Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements—0
Decomposing Word Embedding with the Capsule Network—0
Deconstructing and reconstructing word embedding algorithms—0
Deconstructing Complex Search Tasks: a Bayesian Nonparametric Approach for Extracting Sub-tasks—0
Deconstructing word embedding algorithms—0
Deconstructing Word Embeddings—0
Bingo at IJCNLP-2017 Task 4: Augmenting Data using Machine Translation for Cross-linguistic Customer Feedback Classification—0
Deduplication of Scholarly Documents using Locality Sensitive Hashing and Word Embeddings—0
Deep Bidirectional Transformers for Relation Extraction without Supervision—0
Deep Clustering with Measure Propagation—0
Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing -- A Tale of Two Parsers Revisited—0
Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing - A Tale of Two Parsers Revisited—0
A Comparison of Domain-based Word Polarity Estimation using different Word Embeddings—0
Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts—0
Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations—0
AWE: Asymmetric Word Embedding for Textual Entailment—0
Deeper Attention to Abusive User Content Moderation—0
An Empirical Study of Discriminative Sequence Labeling Models for Vietnamese Text Processing—0
Binary Encoded Word Mover’s Distance—0
A Helping Hand: Transfer Learning for Deep Sentiment Analysis—0
Binary and Multitask Classification Model for Dutch Anaphora Resolution: Die/Dat Prediction—0
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